A Virtual Actor Behavior Model Based on Emotional Biologically Inspired Cognitive Architecture

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Artificial General Intelligence (AGI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13154))

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Abstract

Many digital devices and systems that interact with humans can be expected to become emotional in the coming years. This transition will help them achieve trust and mutual understanding in establishing contacts at the social level, which is necessary for their integration into human society. The main problem is the ability to understand emotions and adequately respond to them: i.e., emotional intelligence, both verbal and non-verbal, which today is fully realized only in biological systems. In this work, four experimental paradigms were used for the development and study of a general model of social-emotional intelligence: a virtual dance partner, a virtual clown improvisation, a virtual pet, and a virtual interlocutor. The virtual actor model implemented the basics of the eBICA cognitive architecture. Characteristics of the virtual actor behavior were evaluated and, when possible, compared against the characteristics of human behavior in the same settings. Preliminary results support the idea of one universal cognitive model applicability to a variety of domains and interaction paradigms involving human and virtual actors. Practical implications of the concept are discussed.

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Acknowledgments

The author is grateful to Vladimir Tsarkov, Vladislav Enikeev, Denis Semenov, Aleksey Mikhnev, Yulianna Karabelnikova, Alexandr Dodonov, Igor Grishin, Anton Budanitsky, Matvey Klychkov, Alyona Anisimova, Egor Korekov, Maxim Abramenko for useful discussions and help with the implementations, experiment running, and data analysis. I am also grateful to all participants of the experiments. This work was supported by the Ministry of Science and Higher Education of the Russian Federation, state assignment project No. 0723-2020-0036.

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Samsonovich, A.V. (2022). A Virtual Actor Behavior Model Based on Emotional Biologically Inspired Cognitive Architecture. In: Goertzel, B., Iklé, M., Potapov, A. (eds) Artificial General Intelligence. AGI 2021. Lecture Notes in Computer Science(), vol 13154. Springer, Cham. https://doi.org/10.1007/978-3-030-93758-4_23

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  • DOI: https://doi.org/10.1007/978-3-030-93758-4_23

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-93758-4

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